VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.

263-4400-00L 5 Credits DR , MSC , WBZ D-ITET , D-INFK , D-MATH
You're viewing possible stale or outdated data. Please check the latest semester for more up-to-date information.

Advanced Graph Algorithms and Optimization

Lecturers & Examiners: Prof. Dr. Rasmus Kyng
Number of participants limited to 30.
VVZ CR 3.8

Last Updated: 2026-02-05 15:42:00

Abstract

This course will cover a number of advanced topics in optimization and graph algorithms.

Objective

The course will take students on a deep dive into modern approaches to graph algorithms using convex optimization techniques. By studying convex optimization through the lens of graph algorithms, students should develop a deeper understanding of fundamental phenomena in optimization. The course will cover some traditional discrete approaches to various graph problems, especially flow problems, and then contrast these approaches with modern, asymptotically faster methods based on combining convex optimization with spectral and combinatorial graph theory.

Content

Students should leave the course understanding key concepts in optimization such as first and second-order optimization, convex duality, multiplicative weights and dual-based methods, acceleration, preconditioning, and non-Euclidean optimization. Students will also be familiarized with central techniques in the development of graph algorithms in the past 15 years, including graph decomposition techniques, sparsification, oblivious routing, and spectral and combinatorial preconditioning.

Resources

Learning Materials (Links)

General Information

Language
English
Levels
DR , MSC , WBZ
Frequency
Yearly recurring

Examination

Type
graded semester performance
Graded Homework 1: 15 % of grade. Homework consists entirely of exercises.Graded Homework 2: 15 % of grade. 10 % is for exercises, 5 % is for a short written report on a paper. The lecturer will assign papers to students, possibly with some input from students. Assignments are done individually.Oral exam: 70 % of the grade. Exam is 30 minutes, of which 15 minutes will be spent on the paper associated with the written report, and 15 minutes will be spent covering topics from the lectures.

Registration & Places

Max Places
30

Course Components

Type Title Time & Place Hours
lecture with exercise Advanced Graph Algorithms and Optimization
  • Wed 09:15-12:00 (CAB G 52)
3 h weekly
independent project Advanced Graph Algorithms and Optimization No time listed 1 h weekly

Offered In